Exchange of water between groundwater and surface water could alter water quality of the surface waters and thereby impact its ecosystem. Discharges of anoxic groundwater, with high concentrations of sulfate and chloride and low concentrations of nitrate and oxygen, from three sinkhole vents (El Cajon, Middle Island and Isolated) in Lake Huron have been recently documented. In this investigation, we collected and analyzed a suite of water samples from these three sinkhole vents and lake water samples from Lake Huron for Ra, radon-222, stable isotopes of oxygen and hydrogen, and other ancillary parameters. These measurements are among the first of their kind in this unique environment. The activities of Ra are found to be one to two orders of magnitude higher than that of the lake water. Isotopic signatures of some of the bottom lake water samples indicate evidences for micro-seeps at distances farther from these three vents. A plot of δD versus δ18O indicates that there are deviations from the Global Meteoric Line that can be attributed to mixing of different water masses and/or due to some subsurface chemical reactions. Using the Ra isotopic ratios, we estimated the transit times of the vent waters from the bottom to the top of the vent (i.e., sediment–water interface) to be 4–37 days. More systematic studies on the distribution of the radioactive and stable isotope studies are needed to evaluate the prevalence of micro-seeps in Lake Huron and other Great Lakes system.

The generation mechanism of meteotsunamis, which are meteorologically induced water waves with spatial/temporal characteristics and behavior similar to seismic tsunamis, is poorly understood. We quantify meteotsunamis in terms of seasonality, causes, and occurrence frequency through the analysis of long-term water level records in the Laurentian Great Lakes. The majority of the observed meteotsunamis happen from late-spring to mid-summer and are associated primarily with convective storms. Meteotsunami events of potentially dangerous magnitude (height > 0.3 m) occur an average of 106 times per year throughout the region. These results reveal that meteotsunamis are much more frequent than follow from historic anecdotal reports. Future climate scenarios over the United States show a likely increase in the number of days favorable to severe convective storm formation over the Great Lakes, particularly in the spring season. This would suggest that the convectively associated meteotsunamis in these regions may experience an increase in occurrence frequency or a temporal shift in occurrence to earlier in the warm season. To date, meteotsunamis in the area of the Great Lakes have been an overlooked hazard.

Human activities are causing a global proliferation of cyanobacterial harmful algal blooms (CHABs), yet we have limited understanding of how these events affect freshwater bacterial communities. Using weekly data from western Lake Erie in 2014, we investigated how the cyanobacterial community varied over space and time, and whether the bloom affected non-cyanobacterial (nc-bacterial) diversity and composition. Cyanobacterial community composition fluctuated dynamically during the bloom, but was dominated by Microcystis and Synechococcus OTUs. The bloom's progression revealed potential impacts to nc-bacterial diversity. Nc-bacterial evenness displayed linear, unimodal, or no response to algal pigment levels, depending on the taxonomic group. In addition, the bloom coincided with a large shift in nc-bacterial community composition. These shifts could be partitioned into components predicted by pH, chlorophyll a, temperature, and water mass movements. Actinobacteria OTUs showed particularly strong correlations to bloom dynamics. AcI-C OTUs became more abundant, while acI-A and acI-B OTUs declined during the bloom, providing evidence of niche partitioning at the sub-clade level. Thus, our observations in western Lake Erie support a link between CHABs and disturbances to bacterial community diversity and composition. Additionally, the short recovery of many taxa after the bloom indicates that bacterial communities may exhibit resilience to CHABs.

Harmful algal blooms (HABs) have increased in frequency and magnitude in western Lake Erie and spring phosphorus (P) load was shown to be a key driver of bloom intensity. A recently developed Bayesian hierarchical model that predicts peak bloom size as a function of Maumee River phosphorus load suggested an apparent increased susceptibility of the lake to HABs. We applied that model to develop load–response curves to inform revision of Lake Erie phosphorus load targets under the 2012 Great Lakes Water Quality Agreement. In this application, the model was modified to estimate the fraction of the particulate P (PP) load that becomes bioavailable, and it was recalibrated with additional bloom observations. Although the uncertainty surrounding the estimate of the bioavailable PP fraction is large, inclusion in the model improves prediction of bloom variability compared to dissolved reactive P (DRP) alone. The ability to characterize model and measurement uncertainty through hierarchical modeling allowed us to show that inconsistencies in bloom measurement represent a considerable portion of the overall uncertainty associated with load–response curves. The updated calibration also lends support to the system's apparent enhanced susceptibility to blooms. The temporal trend estimated by the model results in an upward shift of the load–response curve over time such that a larger load reduction is required to achieve a target bloom size today compared to earlier years. More research is needed to further test the hypothesis of a shift in the lake's response to stressors over time and, if confirmed, to explore underlying mechanisms.

BOLINGER, R.A., A.D. GRONEWOLD, K.A. Kompoltowicz, and L.M. Fry. Application of the NMME in the Development of a New Regional Seasonal Climate Forecast Tool. Bulletin of the American Meteorological Society (DOI:10.1175/BAMS-D-15-00107.1) (2016). (IN PRESS)

With the use of the North American Multi-Model Ensemble, a web-based tool provides useful information to users who rely on seasonal climate forecasts for their operations and decision making.

The National Oceanic and Atmospheric Administration's Climate Prediction Center (NOAA – CPC) provides access to a suite of real-time monthly climate forecasts that comprise the North American Multi-Model Ensemble (NMME), in an attempt to meet the increasing demands for monthly to seasonal climate prediction. While the North American and global map-based forecasts provided by NOAA – CPC are informative on a broad or continental scale, operational and decision-making institutions need products with a much more specific regional focus. To address this need, we developed a Region-specific Seasonal Climate Forecast tool (RSCF-NMME) by combining NMME forecasts with regional climatological data. The RSCF-NMME automatically downloads and archives data, and is displayed via a dynamic web-based graphical user interface. The tool has been applied to the Great Lakes region and utilized as part of operational water level forecasting procedures by the U.S. Army Corps of Engineers, Detroit District (USACE-Detroit). Evaluation of the tool, compared with seasonal climate forecasts released by NOAA – CPC, shows that the tool can provide additional useful information to users and overcomes some of the limitations of the NOAA – CPC forecasts. The RSCF-NMME delivers details about a specific region’s climate, verification observations, and the ability to view different model forecasts. With its successful implementation within an operational environment, the tool has proven beneficial and thus set a precedent for expansion to other regions where there is a demand for region-specific seasonal climate forecasts.

In early August 2014, the municipality of Toledo, OH (USA) issued a ‘do not drink’ advisory on their water supply directly affecting over 400,000 residential customers and hundreds of businesses (Wilson, 2014).

This order was attributable to levels of microcystin, a potent liver toxin, which rose to 2.5 mg L1 in finished drinking water. The Toledo crisis afforded an opportunity to bring together scientists from around the world to share ideas regarding factors that contribute to bloom formation and toxigenicity, bloom and toxin detection as well as prevention and remediation of bloom events. These discussions took place at an NSF- and NOAA-sponsored workshop at Bowling Green State University on April 13 and 14, 2015. In all, more than 100 attendees from six countries and 15 US states gathered together to share their perspectives. The purpose of this review is to present the consensus summary of these issues that emerged from discussions at the Workshop. As additional reports in this special issue provide detailed reviews on many major CHAB species, this paper focuses on the general themes common to all blooms, such as bloom detection, modeling, nutrient loading, and strategies to reduce nutrients.

We propose a bivariate Bayesian hierarchical model (BBHM), which adds a perspective on a century-long subject of research, nitrogen (N) and phosphorus (P) dynamics in freshwater and coastal marine ecosystems. The BBHM is differentiated from existing approaches by modeling multiple aspects of N-P relationships-N and P concentration variability, ratio, and correlation-simultaneously, allowing these aspects to vary by seasonal and/or spatial components. The BBHM is applied to three aquatic systems, Finnish Lakes, Saginaw Bay, and the Neuse Estuary, which exhibit differing landscapes and complexity of nutrient dynamics. Our model reveals N and P dynamics that are critical to inferring unknown N and P distributions for the overall system as well as for within system variability. For Finnish lakes, strong positive within- and among-lake N and P correlations indicate that the rates of N and P biogeochemical cycles are closely coupled during summer across the different lake categories. In contrast, seasonal decoupling between N and P cycles in Saginaw Bay is evidenced by the large variability in monthly correlations and the seasonal changes in the N distribution. The results underscore the pivotal role that dreissenids have had on the cycling of nutrients and resurgence of eutrophication. The presence of clear seasonality and a spatial gradient in the distributions and N and P in the Neuse Estuary suggest that riverine N input is an important source in the season-space N dynamics, while summer sediment release is a major process regulating seasonal P distribution.

Modeling to accurately predict river phytoplankton distribution and abundance is important in water quality and resource management. Nevertheless, the complex nature of eutrophication processes in highly connected river systems makes the task challenging. To model dynamics of river phytoplankton, represented by chlorophyll a (Chl a) concentration, we propose a Bayesian hierarchical model that explicitly accommodates seasonality and upstream-downstream spatial gradient in the structure. The utility of our model is demonstrated with an application to the Nakdong River (South Korea), which is a eutrophic, intensively regulated river, but functions as an irreplaceable water source for more than 13 million people. Chl a is modeled with two manageable factors, river flow, and total phosphorus (TP) concentration. Our model results highlight the importance of taking seasonal and spatial context into account when describing flow regimes and phosphorus delivery in rivers. A contrasting positive Chl a-flow relationship across stations versus negative Chl a-flow slopes that arose when Chl a was modeled on a station-month basis is an illustration of Simpson's paradox, which necessitates modeling Chl a-flow relationships decomposed into seasonal and spatial components. Similar Chl a-TP slopes among stations and months suggest that, with the flow effect removed, positive TP effects on Chl a are uniform regardless of the season and station in the river. Our model prediction successfully captured the shift in the spatial and monthly patterns of Chl a.

In a world of increasing interconnections in global trade as well as rapid change in climate and land cover, the accelerating introduction and spread of invasive species is a critical concern due to associated negative social and ecological impacts, both real and perceived. Much of the societal response to invasive species to date has been associated with negative economic consequences of invasions. This response has shaped a war-like approach to addressing invasions, one with an agenda of eradications and intense ecological restoration efforts towards prior or more desirable ecological regimes. This trajectory often ignores the concept of ecological resilience and associated approaches of resilience-based governance. We argue that the relationship between ecological resilience and invasive species has been understudied to the detriment of attempts to govern invasions, and that most management actions fail, primarily because they do not incorporate adaptive, learning-based approaches. Invasive species can decrease resilience by reducing the biodiversity that underpins ecological functions and processes, making ecosystems more prone to regime shifts. However, invasions do not always result in a shift to an alternative regime; invasions can also increase resilience by introducing novelty, replacing lost ecological functions or adding redundancy that strengthens already existing structures and processes in an ecosystem. This paper examines the potential impacts of species invasions on the resilience of ecosystems and suggests that resilience-based approaches can inform policy by linking the governance of biological invasions to the negotiation of tradeoffs between ecosystem services.

Hydrogen peroxide (h1O2) has been suggested to influence cyanobacterial community structure and toxicity. However, no study has investigated h1O2 concentrations in freshwaters relative to cyanobacterial blooms when sources and sinks of h1O2 may be highly variable. For example, photochemical production of h1O2 from chromophoric dissolved organic matter (CDOM) may vary over the course of the bloom with changing CDOM and UV light in the water column, while microbial sources and sinks of h1O2 may change with community biomass and composition. To assess relationships between h1O2 and harmful algal blooms dominated by toxic cyanobacteria in the western basin of Lake Erie, we measured h1O2 weekly at six stations from June to November, 2014 and 2015, with supporting physical, chemical, and biological water quality data. Nine additional stations across the western, eastern, and central basins of Lake Erie were sampled during August and October, 2015. CDOM sources were quantified from the fluorescence fraction of CDOM using parallel factor analysis (PARAFAC). CDOM concentration and source were significantly correlated with specific conductivity, demonstrating that discharge of terrestrially-derived CDOM from rivers can be tracked in the lake. Autochthonous sources of CDOM in the lake increased over the course of the blooms. Concentrations of h1O2 in Lake Erie ranged from 47 ± 16 nM to 1570 ± 16 nM (average of 371 ± 17 nM; n = 225), and were not correlated to CDOM concentration or source, UV light, or estimates of photochemical production of h1O2 by CDOM. Temporal patterns in h1O2 were more closely aligned with bloom dynamics in the lake. In 2014 and 2015, maximum concentrations of h1O2 were observed prior to peak water column respiration and chlorophyll a, coinciding with the onset of the widespread Microcystis blooms in late July. The spatial and temporal patterns in h1O2 concentrations suggested that production and decay of h1O2 from aquatic microorganisms can be greater than photochemical production of h1O2 from CDOM and abiotic decay pathways. Our study measured h1O2 concentrations in the range where physiological impacts on cyanobacteria have been reported, suggesting that h1O2 could influence the structure and function of cyanobacterial communities in Lake Erie.

A thorough assessment of aquatic nonindigenous species’ risk facilitates successful monitoring and prevention activities. However, species- and vector-specific information is often limited and difficult to synthesize across a single risk framework. To address this need, we developed an assessment framework capable of estimating the potential for introduction, establishment, and impact by aquatic nonindigenous species from diverse spatial origins and taxonomic classification, in novel environments. Our model builds on previous approaches, while taking on a new perspective for evaluation across species, vectors and stages to overcome the limitations imposed by single species and single vector assessments. We applied this globally-relevant framework to the Laurentian Great Lakes to determine its ability to evaluate risk across multiple taxa and vectors. This case study included 67 aquatic species, identified as “watchlist species” in NOAA’s Great Lakes Aquatic Nonindigenous Species Information System (GLANSIS). Vectors included shipping, hitchhiking/fouling, unauthorized intentional release, escape from recreational or commercial culture, and natural dispersal. We identified potential invaders from every continent but Africa and Antarctica. Of the 67 species, more than a fifth (21%) had a high potential for introduction and greater than 60% had a moderate potential for introduction. Shipping (72%) was the most common potential vector of introduction, followed by unauthorized intentional release (25%), hitchhiking/fouling (21%), dispersal (19%), stocking/planting/escape from recreational culture (13%), and escape from commercial culture. The ability to assess a variety of aquatic nonindigenous species from an array of potential vectors using a consistent methodology is essential for comparing likelihoods of introduction, establishment, and impact. The straightforward design of this framework will allow its application and modification according to policy priorities by natural resource managers. The ability to use a variety of information sources facilitates completion of assessments despite the paucity of data that often plagues aquatic nonindigenous species management.

The Chloroflexi CL500-11 clade predominates bacterial biomass in oxygenated hypolimnia of deep lakes worldwide, including the world's largest freshwater system, the Laurentian Great Lakes. Trains that allow CL500-11 to thrive and its biochemical role in these environments are currently unknown. Here, we found that a CL500-11 population was mostly present in off-shore waters along a transect in ultra-oligotrophic Lake Michigan (a Laurentian Great Lake). It occurred throughout the water column in spring, and only in the hypolimnion during summer stratification, contributing up to 18.1% of all cells. Genome reconstruction from metagenomic data suggested an aerobic, motile, heterotrophic lifestyle with additional energy gained through carboxidovory and methylovory. Comparisons to other available streamlined freshwater genomes revealed that CL500-11 contains disproportionate number of cell wall/capsule biosynthesis genes and the most diverse DOM substrate uptake spectrum, particularly for peptides. In situ expression patterns indicate the importance of DOM uptake and protein/peptide turnover, as well as Type I and Type II carbon monoxide dehydrogenase and flagellar motility. Location in the water column influenced expression patterns most, marked by increased bacteriorhodospin expression and a response to oxidative stress in surface compared to deep waters. While carrying multiple adaptations to an oligotrophic and mesotrophic lakes indicate the ability to thrive under conditions where resources are more plentiful. Our data indicate that CL500-11 plays an important role in nitrogen-rich DOM mineralization in the extensive deep lake hypolimnion habitat.

Summary: 1. Ecosystems are complex and multivariate; hence, methods to assess the dynamics ofecosystems should have the capacity to evaluate multiple indica tors simultaneously. 2. Most research on identifying leading indicators of regime shifts has focused on univariatemethods and simple models which have limited utility when evaluating real ecosystems, par-ticularly because drivers are often unknown. 3. We discuss some common univariate and multivariate approaches for detecting criticaltransitions in ecosystems and demonstrate their capabilities via case studies. 4. Synthesis and applications. We illustrate the utility of an information theory-based indexfor assessing ecosystem dynamics. Trends in this index also provide a sentinel of both abruptand gradual transitions in ecosystems.

FAHNENSTIEL, G.L., M.J. Sayers, R.A. Shuchman, F. Yousef, and S.A. POTHOVEN. Lake-wide phytoplankton production and abundance in the upper Great Lakes: 2010-2013. Journal of Great Lakes Research 42(3):619-629 (DOI:10.1016/j.jglr.2016.02.004) (2016).

Lake-wide phytoplankton chlorophyll a concentrations and primary production were determined for lakes Huron, Michigan, and Superior in 2010–2013. Chlorophyll a concentrations were determined using MODIS imagery with a color-producing agent algorithm and primary production with the Great Lakes Production Model using remotely sensed and empirically derived input from the Upper Great Lakes. The new chlorophyll a and primary production estimates agreed well with field measurements. Lake-wide mean chlorophyll a concentrations determined from observations in all 12 months were highest in Lake Superior (mean = 0.99 mg/m3), intermediate in Lake Michigan (mean = 0.88 mg/m3), and lowest in Lake Huron (mean = 0.77 mg/m3). In Lake Superior, a gradient in chlorophyll a concentrations was noted from the shallow zone (0–30 m, mean = 1.57 mg/m3) to the deep-water zone (> 150 m, mean = 0.94 mg/m3). However, in Lake Michigan, no differences in mean chlorophyll a concentrations were noted in shallow-, mid-, or deep-water zones (means, 0.83, 0.86, 0.90 mg/m3, respectively). Lake-wide areal integrated primary production rates in lakes Huron, Michigan, and Superior were not significantly different for the 2010–2013 period (means, 216, 259, and 228 mg C/m2/d, respectively). Also, primary production in all depth zones (shallow, mid, and deep) were similar across lakes. Annual whole-lake phytoplankton carbon fixation values for 2010–2013 ranged from 4.4 to 5.7 Tg/y for Lake Huron, 5.0–7.2 Tg/y for Lake Michigan, and 6.4–9.5 Tg/y for Lake Superior.

Invasive dreissenid mussels (D. polymorpha and D. r. bugensis) have fundamentally altered Laurentian Great Lake ecosystems, however in many areas their abundances have declined since the mid-1990s. Another invader, the benthic fish round goby (Neogobius melanostomus), is morphologically adapted to feed on dreissenids and likely affects dreissenid populations; however, the degree of this predatory effect is variable. In 2009 and 2010, we examined round goby abundances, size distributions, diet contents, and diet selectivity in Saginaw Bay, Lake Huron; a shallow bay that has been subjected to numerous anthropogenic stressors. We further used a consumption model to estimate dreissenid consumption by three different size classes of round goby. Round gobies were found throughout the bay and most were smaller than 80 mm total length. Round gobies of all sizes consumed dreissenids (including fish as small as 30 mm total length), though dreissenids were rarely preferred. The relative proportion of dreissenids (by biomass) present in diets of round gobies increased with fish size, but also throughout the year for all size classes. Despite this, overall consumptive effects of round gobies on dreissenids in Saginaw Bay were low. Many dreissenids present in the bay were larger than those consumed by round gobies. Bioenergetics-based model estimates suggest that the smallest round gobies are responsible for the majority of dreissenid consumption. While our findings are limited to soft substrates and influenced by sampling restrictions, our study design allowed us to put bounds on our estimates based upon these multiple sources of uncertainty.

Freshwater bacteria play key roles in biogeochemical cycling and contribute significantly to biomass and energy fluxes. However, studies of Great Lakes ecosystem dynamics often omit bacteria. Here, we used high throughput sequencing to analyze how bacterial diversity and community composition (BCC) vary seasonally along the long-term Muskegon estuary to pelagic research transect. Diversity was higher in the estuary than Lake Michigan, in spring compared to summer, and for particle-associated (PA) relative to free-living (FL) fractions. PA communities were distinct from and more variable than FL communities. For both fractions, spring BCC was more similar between estuary and nearshore Lake Michigan compared to offshore waters. In summer and fall, nearshore and offshore BCC were more similar compared to estuary BCC. Most abundant taxa were inferred to be chemoorganoheterotrophs. While, as a whole, this functional group only showed habitat preference for the PA fraction, we observed phylum- and class-level seasonal and spatial preferences. Chemoorganoheterotrophs that also perform bacteriorhodopsin-mediated phototrophy, such as acI Actinobacteria and LD12, strongly preferred FL fractions. Photoautotrophs (Cyanobacteria) were least abundant in spring, when mixotrophic methylotrophs were more abundant, particularly in the estuary. Organisms with chemolithotrophic capabilities, including a mixotrophic, highly abundant Limnohabitans (Lhab-A1) OTU, showed limited spatiotemporal patterns. One exception was Nitrosospira, an autotrophic ammonium oxidizer, which peaked in deep offshore waters in fall. Nitrosospira co-occurred with Chloroflexi CL500-11, which likely mineralizes nitrogen-rich organic matter in deep waters. These spatiotemporal BCC shifts suggest differences in bacterially mediated elemental cycling along estuary to pelagic gradients in Lake Michigan.

Introduced species have the potential for both ecological and socioeconomic effects. Once established, these species can be nearly impossible to eradicate (Hobbs & Humphries 1995). In the few successful eradication efforts, the cost has been substantial (Simberloff 2003). Managing spread and controlling for impact are also costly (Leung et al. 2002). At least 31% nonindigenous species established in the Great Lakes have significant impacts (Sturtevant et al. 2014). The most economically and practically effective strategy is therefore to prevent species introduction in the first place (Lodge et al. 2006). As a means of prioritizing management efforts, risk assessment tools that consider vectors and pathways of introduction, species life history traits, habitat suitability, historical patterns of invasion, impacts realized in other invaded regions have become commonly implemented (Gordon et al. 2012, Keller et al. 2009). In order to accurately predict risk, a thorough understanding of these potentially introduced species is needed (Keller et al. 2007b, Springborn et al. 2011—but see Simberloff 2003). However, species and pathway information can also be scarce or diffuse (e.g., 95/156 species assessed as “not enough known” in USEPA 2008).

The Great Lakes Runoff Inter-comparison Project for Lake Ontario (GRIP-O) aims to compare different hydrologic models, using the same settings, in their ability to estimate runoff for the Lake Ontario watershed. The watershed is challenging because many of its tributaries have a regulated flow regime and a significant part remains ungauged. GRIP-O follows the GRIP-M project which focused on Lake Michigan. It involves a comparison between two different sources of precipitation data (CaPA - Canadian Precipitation Analysis and the GHCND - Global Historical Climatology Network - Daily), and focuses here on two lumped models, GR4J (modèle du Génie Rural à 4 paramètres Journalier) and LBRM (Large Basin Runoff Model).

Results indicate that both models perform very well, with GR4J performing slightly better than LBRM and the GHCND precipitation dataset resulting in better simulations than CaPA, for this area. Performances are, however, always very satisfactory whatever the combination of model/precipitation data used, even for regulated catchments, and do not show any clear correlation to any of the catchments' properties studied here. Results also tend to confirm that the Area-Ratio Method is appropriate for extrapolating flows from the gauged part of a catchment to the whole catchment including its ungauged parts, as demonstrated in GRIP-M.

This work describes the implementation of the distributed GEM-Hydro runoff modeling platform, developed at Environment and Climate Change Canada (ECCC) over the last decade. The latest version of GEM-Hydro combines the SVS (Soil, Vegetation and Snow) land-surface scheme and the WATROUTE routing scheme in order to provide streamflow predictions on a gridded river network. SVS is designed to be two-way coupled to the GEM (Global Environmental Multi-scale) atmospheric model exploited by ECCC for operational weather and environmental forecasting. Although SVS has been shown to accurately track soil moisture during the warm season, it has never been evaluated before for hydrological prediction. This paper presents a first evaluation of its ability to simulate streamflow for all major rivers flowing into Lake Ontario. The skill level of GEM-Hydro is assessed by comparing the quality of simulated flows to that of two established hydrological models, MESH and WATFLOOD, which share the same routing scheme (WATROUTE) but rely on different land–surface schemes. All models are calibrated using the same meteorological forcings, objective function, calibration algorithm, and watershed delineation. Results show that GEM-Hydro performs well and is competitive with MESH and WATFLOOD. A computationally efficient strategy is proposed to calibrate the land-surface model of GEM-Hydro: a simple unit hydrograph is used for routing instead of its standard distributed routing component. The distributed routing part of the model can then be run in a second step to estimate streamflow everywhere inside the domain. Global and local calibration strategies are compared in order to estimate runoff for ungauged portions of the Lake Ontario watershed. Overall, streamflow predictions obtained using a global calibration strategy, in which a single parameter set is identified for the whole watershed of Lake Ontario, show skills comparable to the predictions based on local calibration. Hence, global calibration provides spatially consistent parameter values, robust performance at gauged locations, and reduces the complexity and computational burden of the calibration procedure. This work contributes to the Great Lakes Runoff Inter-comparison Project for Lake Ontario (GRIP-O) which aims at improving Lake Ontario basin runoff simulations by comparing different models using the same input forcings.

Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments – since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins – especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll-a (Chl-a) or phycocyanin (PC) collected in situ as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl-a. Where cyanobacteria dominate, Chl-a is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MCpigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl-a concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameteriza- tions between lakes. A strategy for producing useful estimates of microcystins from cyanobacterial biomass is described, provided cyanotoxin variability is addressed.

Introduction to the Great Lakes hydrological system. The North American Great Lakes system is commonly defined, as shown in figure 121-1, as the international waters of the Great Lakes themselves (i.e. Lakes Superior, Michigan, Huron, Erie, and Ontario), the rivers that connect them (commonly referred to as `interconnecting channels’), and their surrounding drainage areas. Generally, water flows through the system from Lake Superior through the St. Marys River, as shown in figure 121-2, to Lake Michigan-Huron (Lake Michigan and Lake Huron are often considered one lake because of their connection at the Straits of Mackinac). From Lake Huron, water flows through the St. Clair River, through Lake St. Clair, and through the Detroit River into Lake Erie. Water then flows out of Lake Erie through the Niagara River and over Niagara Falls into Lake Ontario. The downstream boundary of the Great Lakes is often defined as the outlet of Lake Ontario, as reflected in figure 121-1. However, the downstream boundary of the Great Lakes system is also sometimes defined by the Moses-Saunders dam (the point at which outflows from Lake Ontario are regulated), located along the St. Lawrence River at Cornwall, Ontario (Canada) and Massena, NY (USA). For further reading on the St. Lawrence River system downstream of the Great Lakes, see Chapter 113. The Great Lakes constitute the largest (both by volume and surface area) system of lakes on Earth (Herdendorf, 1990; Quinn, 1992). Lake Michigan-Huron alone has the largest continuous surface area (117,250 km2) of any freshwater surface body on Earth, while Lake Superior has the second largest surface area (82,100 km2). The total volume of the Great Lakes (roughly 22,800 km3) is very close to the volume of Lake Baikal, Earth’s largest lake by volume (roughly 23,000 km3), and is slightly larger than that of Lake Tanganyika (18,900 km3). Together, these three systems (the Great Lakes, Lake Tanganyika, and Lake Baikal) comprise about half of all of the fresh surface water on Earth.

Abstract Between January 2013 and December 2014, water levels on Lake Superior and Lake Michigan-Huron, the two largest lakes on Earth by surface area, rose at the highest rate ever recorded for a 2 yearperiod beginning in January and ending in December of the following year. This historic event coincidedwith below-average air temperatures and extensive winter ice cover across the Great Lakes. It also broughtan end to a 15 year period of persistently below-average water levels on Lakes Superior and Michigan-Huron that included several months of record-low water levels. To differentiate hydrological drivers behindthe recent water level rise, we developed a Bayesian Markov chain Monte Carlo (MCMC) routine for inferringhistorical estimates of the major components of each lake’s water budget. Our results indicate that, in 2013,the water level rise on Lake Superior was driven by increased spring runoff and over-lake precipitation. In2014, reduced over-lake evaporation played a more signiﬁcant role in Lake Superior’s water level rise. Thewater level rise on Lake Michigan-Huron in 2013 was also due to above-average spring runoff and persistentover-lake precipitation, while in 2014, it was due to a rare combination of below-average evaporation,above-average runoff and precipitation, and very high inﬂow rates from Lake Superior through the St. MarysRiver. We expect, in future research, to apply our new framework across the other Laurentian Great Lakes,and to Earth’s other large freshwater basins as well.

While toxic cyanobacterial blooms in western Lake Erie threaten drinking water supplies and are promoted by nutrient loading, the precise nutrient regime that selects specific cyanobacteria populations is poorly understood. Here, we assess shifts in cyanobacterial abundances and global gene expression patterns in response to natural and manipulated gradients in nitrogen and phosphorus to identify gene pathways that facilitate dominance by different cyanobacteria. Gradients in soluble reactive phosphorus shaped cyanobacterial communities and elicited the largest transcriptomic responses. Under high P conditions (closest to the mouth of the Maumee River), Anabaena and Planktothrix were the dominant cyanobacterial populations and experimental P and ammonium enrichment promoted nitrogen fixation gene (nifH) expression in Anabaena. For Microcystis, experimental additions of P upregulated genes involved in phage defense, genomic rearrangement, and nitrogen acquisition, but led to lower abundances. Within offshore, low P regions of the western basin of Lake Erie, Microcystis upregulated genes associated with P scavenging (pstSCAB, phoX) and dominated cyanobacterial communities. Experimental additions of ammonium and urea did not alter Microcystis abundances but did upregulate protease inhibitors (aer, mcn gene sets) and microcystin synthetase genes (mcy) with urea enrichment yielding significant increases in microcystin concentrations. Our findings suggest that management plans that reduce P loads alone may not significantly reduce the risk of cyanobacterial blooms in western Lake Erie, but rather may promote a shift among cyanobacterial populations (Microcystis, Anabaena, and Planktothrix) towards a greater dominance by toxic strains of Microcystis.

Time series measurements of ice thickness were made at 6 moorings located in the central basin of Lake Erie during the winter of 2010-2011. ASL shallow water ice profilers (SWIPS) units were deployed at 4 stations and Nortek AWACS profilers equipped with ice measurement software were deployed at 3 stations. At one station both a SWIPs and an AWACS unit were deployed. Ice formation began in the central basin in early January of 2011 and the entire basin was ice-covered by the end of the month. Ice cover continued until the end of the March but was not continuous at any of the stations. There was a pronounced thaw in mid-February when the ice cover all but vanished. The ice was not shore-fast and ice thicknesses varied widely at all of the stations over periods of minutes to hours. Maximum thicknesses reached over 4 m in some instances. There is little correlation of the thicknesses between the stations or between the two instruments co-located at one station. The extreme variability of the measurements makes it difficult to determine a meaningful daily ice thickness.

A three-dimensional physical-biological model has been used to simulate seasonal phytoplankton variations in the Bering and Chukchi Seas with a focus on understanding the physical and biogeochemical mechanisms involved in the formation of the Bering Sea Green Belt (GB) and the Subsurface Chlorophyll Maxima (SCM). Model results suggest that the horizontal distribution of the GB is controlled by a combination of light, temperature, and nutrients. Model results indicated that the SCM, frequently seen below the thermocline, exists because of a rich supply of nutrients and sufficient light. The seasonal onset of phytoplankton blooms is controlled by different factors at different locations in the Bering-Chukchi Sea. In the off-shelf central region of the Bering Sea, phytoplankton blooms are regulated by available light. On the Bering Sea shelf, sea ice through its influence on light and temperature plays a key role in the formation of blooms, whereas in the Chukchi Sea, bloom formation is largely controlled by ambient seawater temperatures. A numerical experiment conducted as part of this study revealed that plankton sinking is important for simulating the vertical distribution of phytoplankton and the seasonal formation of the SCM. An additional numerical experiment revealed that sea ice algae account for 14.3–36.9% of total phytoplankton production during the melting season, and it cannot be ignored when evaluating primary productivity in the Arctic Ocean.

Scientists who are skilled in communication reap professional and personal rewards. Unfortunately, gaps exist in fostering curricular and extracurricular training in science communication. We focus our article on opportunities for university- and department-level leadership to train new scientists to communicate effectively. Our motivation is threefold: (1) communication training is key to being competitive in the increasingly diverse job market, (2) training early career scientists in communication “jump-starts” personal and societal benefits, and (3) the authors represent a group of early career aquatic scientists with unique insights on the state of and need for training. We surveyed early career aquatic scientists about their science communication training experiences. In summary, survey respondents indicated that (1) science communication training is important; (2) graduate students are interested in training that is not currently available to them; (3) departments and advisors are moderately supportive of students participating in science communication, but less enthusiastic about providing training support; and (4) graduate students lack opportunities to put science communication training into practice. We recommend departments and institutions recognize the benefits of science communication training, develop a strategy to support such training, and facilitate individualized approaches to science communication.

Food web models are powerful tools to inform management of lake ecosystems, where top-down (predation) and bottom-up (resource) controls likely propagate through multiple trophic levels because of strong predator–prey links. We used the Ecopath with Ecosim modeling approach to assess these controls on the Lake Huron main basin food web and the 2003 collapse of an invasive pelagic prey fish, alewife (Alosa pseudoharengus). We parameterized two Ecopath models to characterize food web changes occurring between two study periods of 1981–1985 and 1998–2002. We also built an Ecosim model and simulated food web time-dynamics under scenarios representing different levels of top-down control by Chinook salmon (Oncorhynchus tshawytscha) and of bottom-up control by quagga mussels (Dreissena rostriformis bugensis) and nutrients. Ecopath results showed an increase in the relative importance of bottom-up controls between the two periods, as production decreased across all trophic levels. The production of non-dreissenid benthos decreased most, which could cause decreases in production of pelagic prey fishes feeding on them. Ecosim simulation results indicated that the alewife collapse was caused by a combination of top-down and bottom-up controls. Results showed that while controls by Chinook salmon were relatively constant before alewife collapse, controls by quagga mussels and nutrients increased jointly to unsustainable levels. Under current conditions of low nutrients and high quagga mussel biomass, simulation results showed that recovery of alewives is unlikely regardless of Chinook salmon biomass in Lake Huron, which implies that the shrinking prey base cannot support the same level of salmonine predators as that prevailed during the 1980s.

The expected impacts of invasive species are key considerations in selecting policy responses to potential invasions. But predicting the impacts of invasive species is daunting, particularly in large systems threatened by multiple invasive species, such as North America’s Laurentian Great Lakes. We developed and evaluated a scenario-building process that relied on an expert panel to assess possible future impacts of aquatic invasive species on recreational fishing in the Great Lakes. To maximize its usefulness to policy makers, this process was designed to be implemented relatively rapidly and considered a range of species. The expert panel developed plausible, internally consistent invasion scenarios for five aquatic invasive species, along with subjective probabilities of those scenarios. We describe these scenarios and evaluate this approach for assessing future invasive species impacts. The panel held diverse opinions about the likelihood of the scenarios, and only one scenario with impacts on sport fish species was considered likely by most of the experts. These outcomes are consistent with the literature on scenario building, which advocates for developing a range of plausible scenarios in decision-making because the uncertainty of future conditions makes the likelihood of any particular scenario low. We believe that this scenario-building approach could contribute to policy decisions about whether and how to address the possible impacts of invasive species. In this case, scenarios could allow policy makers to narrow the range of possible impacts on Great Lakes fisheries they consider and help set a research agenda for further refining invasive species predictions.

A four-buoy array was deployed in August 2010 to measure differential ice motion and to assess ice kinematics in light of environmental conditions from the central Arctic Ocean into the Fram Strait. The dynamic setting of the Transpolar Drift Stream (TDS) and the Fram Strait shaped the ice motion and deformation. On a synoptic scale, the ice drift was largely forced by surface winds, with atmospheric forcing accounting for 33-71% of ice-drift variability. Ice drift was closely aligned with the surface winds, except during quiescent conditions, or at times when the wind direction reversed from the dominant direction, i.e., anomalous winds blow against the TDS under the negative Arctic atmospheric Diplole Anomaly (DA). The inertially-induced ice motion weakened gradually from the zone of compacted ice to the marginal ice zone. As ice drifted south of the Fram Strait, its concentration dropped quite dramatically, the ice speed increased, and ice trajectories became more straightforward. As sea ice drifted through the Fram Strait, the acceleration and convergence of the ice was responsible for further substantial ice-field deformation. From a comparison between our updated ice kinematic data and the historic data from 1990, we find that the ice-drift time from the central Arctic Ocean into the Fram Strait was at a low level after 2007, and the ice-drift time can be explained by a monthly mean DA index at the 99% significance level. The DA-derived wind anomalies more effectively influence the ice-drift time via accelerating meridional ice velocity and reducing the curvature of ice-drift trajectory, compared to zonal sea ice divergence (convergence) caused by the positive (negative) phase of Arctic Oscillation (AO).

Measurements of ice type, concentration, thickness, and transmittance are essential for modeling ice growth, wintertime primary productivity estimates, as well as for Coast Guard ice breaking operations in the Great Lakes. This paper describes the use of optical, synthetic aperture radar (SAR), and scatterometer sensors to retrieve those measurements from satellite and airborne platforms. Initial validation of a satellite SAR algorithm to classify Great Lakes ice types showed that ice types can be classified using a library of ice backscatter signatures, but that open water can be misclassified owing to the ambiguity in single polarization data due to variations in wind speed/direction over water. RADARSAT-2 Quad-pol data was used to first create an ice/water mask for both small and large incidence angle SAR data. However, distinguishing ice and water is problematic using RADARSAT-2 ScanSAR Wide data owing to the wide range of incident angles in the data. Using Moderate-Resolution Imaging Spectroradiometer (MODIS) thermal infrared data to distinguish ice and water by surface temperature can remediate the ambiguity, after which the backscatter library can be used to classify ice types. Ice and water can also be identified using dual polarized scatterometer data as well as ice freeze-up and break-up dates. Over open water in Lake Superior, RADARSAT-2 SAR revealed features corresponding to cloud streets in MODIS observations. To aid in estimating lake-wide photosynthetically active radiation (PAR) transmittance through ice, in situ measurements of PAR (400-700 nm) transmittance through major ice types can be used with the maps of ice type to estimate lake-wide transmittance. Until satellite algorithms are developed for ice thickness retrieval, an airborne ground penetrating radar (GPR) can acquire ice thickness transects more effectively than in situ measurement methods. Test flights of a GPR on a helicopter over snow ice/lake ice were made producing acceptably accurate ice thickness. Autonomous drones, tested in March 2016 for real-time ice reconnaissance, may serve as a platform for GPR measurements.

The characteristics and evolution of a satellite-observed anticyclonic eddy in the northern Bering Sea during March and April 1999 are investigated using a three-dimensional Princeton Ocean Model (POM). The anticyclonic-like current pattern and asymmetric feature of the eddy were clearly seen in the synthetic aperture radar (SAR), sea surface temperature, and ocean color images in April 1999. The results from model simulation reveal the three-dimensional structure of the anticyclonic eddy, its movement, and dissipation. Energy analysis indicates that the barotropic instability (BTI) is the main energy source for the growth of the anticyclonic eddy. The momentum analysis further reveals that the larger magnitude of the barotropic pressure gradient in the meridional direction causes the asymmetry of the anticyclonic eddy in the zonal and meridional directions, while the different magnitudes of the meridional baroclinic pressure gradient are responsible for the different intensity of currents between the northern and southern parts of the anticyclonic eddy.

Risk analysis of species invasions links biology and economics, is increasingly mandated by international and national policies, and enables improved management of invasive species. Biological invasions proceed through a series of transition probabilities (i.e., introduction, establishment, spread, and impact), and each of these presents opportunities for management. Recent research advances have improved estimates of probability and associated uncertainty. Improvements have come from species-specific trait-based risk assessments (of estimates of introduction, establishment, spread, and impact probabilities, especially from pathways of commerce in living organisms), spatially explicit dispersal models (introduction and spread, especially from transportation pathways), and species distribution models (establishment, spread, and impact). Results of these forecasting models combined with improved and cheaper surveillance technologies and practices [e.g., environmental DNA (eDNA), drones, citizen science] enable more efficient management by focusing surveillance, prevention, eradication, and control efforts on the highest-risk species and locations. Bioeconomic models account for the interacting dynamics within and between ecological and economic systems, and allow decision makers to better understand the financial consequences of alternative management strategies. In general, recent research advances demonstrate that prevention is the policy with the greatest long-term net benefit.

A method for projecting the water levels of the Laurentian Great Lakes under scenarios of human-caused climate change, used almost to the exclusion of other methods in the past, relies very heavily on the large basin runoff model (LBRM) as a component for determining the water budget for the lake system. This model uses near-surface air temperature as a primary predictor of evapotranspiration (ET); as in previous published work, it is shown here that the model’s very high sensitivity to temperature causes it to overestimate ET in a way that is greatly at variance with the fundamental principle of conservation of energy at the land surface. The traditional formulation is characterized here as being equivalent to having several suns in the virtual sky created by LBRM. More physically based methods show, relative to the traditional method, often astoundingly less potential ET and less ET, more runoff from the land and net basin supply for the lake basins, and higher lake water levels in the future. Using various methods of estimating the statistical significance, it is found that, at minimum, these discrepancies in results are significant at the 99.998% level. The lesson for the larger climate impact community is to use caution about whether an impact is forced directly by air temperature itself or is significantly forced by season or latitude independently of temperature. The results here apply only to the water levels of the Great Lakes and the hydrology of its basin and do not affect larger questions of climate change.

Comparison of polychlorinated biphenyl (PCB) concentrations between the sexes of mature fish may reveal important behavioral and physiological differences between the sexes. We determined whole-fish PCB concentrations in 23 female summer flounder Paralichthys dentatus and 27 male summer flounder from New Jersey coastal waters. To investigate the potential for differences in diet or habitat utilization between the sexes, carbon and nitrogen stable isotope ratios were also determined. In 5 of the 23 female summer flounder, PCB concentrations in the somatic tissue and ovaries were determined. In addition, we used bioenergetics modeling to assess the contribution of the growth dilution effect to the observed difference in PCB concentrations between the sexes. Whole-fish PCB concentrations for females and males averaged 87 and 124 ng/g, respectively; thus males were 43% higher in PCB concentration compared with females. Carbon and nitrogen stable isotope ratios did not significantly differ between the sexes, suggesting that diet composition and habitat utilization did not vary between the sexes. Based on PCB determinations in the somatic tissue and ovaries, we predicted that PCB concentration of females would increase by 0.6%, on average, immediately after spawning due to release of eggs. Thus, the change in PCB concentration due to release of eggs did not explain the higher PCB concentrations observed in males. Bioenergetics modeling results indicated that the growth dilution effect could account for males being 19% higher in PCB concentration compared with females. Thus, the bulk of the observed difference in PCB concentrations between the sexes was not explained by growth dilution. We concluded that a higher rate of energy expenditure in males, stemming from greater activity and a greater resting metabolic rate, was most likely the primary driver for the observed difference in PCB concentrations between the sexes.

This study conducts ice-ocean coupled simulations for the Arctic Ocean, with the nested region of the Eastern Siberian Sea with 4km horizontal resolution. The ocean model is based on the Princeton Ocean Model. The ice dynamic model is based on the elastic-viscous-plastic rheology and the ice thermodynamics is based on the one-dimensional 0-layer model. These models are fully parallelized using the Message-Passing Interface. Initial conditions for ocean and sea ice, as well as atmospheric forcing, are provided by NCEP Climate Forecast System Reanalysis. The simulation will ultimately incorporate data assimilation of hydrographic data from the Russian-American Long-term Census of the Arctic (RUSALCA) cruises. The study will present an initial hindcast simulation from 2000 to 2015 with basic model validation based on comparison with satellite observations.

The effects of climate change on north temperate freshwater ecosystems include increasing water temperatures and decreasing ice cover. Here we compare those trends in the Laurentian Great Lakes at three spatial scales to evaluate how warming varies across the surface of these massive inland water bodies. We compiled seasonal ice cover duration (1973–2013) and lake summer surface water temperatures (LSSWT; 1994–2013), and analyzed spatial patterns and trends at lake-wide, lake sub-basin, and fine spatial scales and compared those to reported lake- and basin-wide trends. At the lake-wide scale we found declining ice duration and warming LSSWT patterns consistent with previous studies. At the lake sub-basin scale, our statistical models identified distinct warming trends within each lake that included significant breakpoints in ice duration for 13 sub-basins, consistent linear declines in 11 sub-basins, and no trends in 4 sub-basins. At the finest scale, we found that the northern- and eastern-most portions of each Great Lake, especially in nearshore areas, have experienced faster rates of LSSWT warming and shortening ice duration than those previously reported from trends at the lake scale. We conclude that lake-level analyses mask significant spatial and temporal variation in warming patterns within the Laurentian Great Lakes. Recognizing spatial variability in rates of change can inform both mechanistic modeling of ecosystem responses and planning for long-term management of these large freshwater ecosystems.

Winter circulation exerts a strong control on the release and timing of nutrients and contaminants from bays into the adjoining lakes. To estimate winter residence times of solutes in the presence of ice cover, we used an ice model coupled to hydrodynamic, thermal and solute transport models of Saginaw Bay and Lake Huron for two low (2010 and 2013) and two high (2009 and 2014) ice years. The models were tested using temperature data from thermistor chains and current data from ADCP moorings deployed during the wintertime. Simulated water temperatures compared favorably to lake-wide average surface temperatures derived from NOAA's AVHRR satellite imagery. Simulated results of ice cover are in agreement with observed data from the Great Lakes Ice Atlas. Our results indicate that ice cover significantly dampens water movement producing almost stagnant conditions around February. Estimates of residence times for Saginaw Bay (defined as the e-folding flushing time based on vertically integrated dye concentrations) show that the mean residence times in a low ice year (2013) are 2.2 months for the inner bay, and 3.5 months for the entire bay. The corresponding numbers for a high ice year (2014) are 4.9 and 5.3 months, respectively. Considering the entire bay, solutes stored in the bay can be expected to be released into the lake between March (low ice year) and April (high ice year). These results are expected to aid in understanding the behavior of contaminants in the Great Lakes during the winter months and in early spring.

POTHOVEN, S.A., and D.B. Bunnell. Shifts in bloater consumption in Lake Michigan between 193 and 2011 and its effects on Diporeia and Mysis prey. Transactions of the American Fisheries Society 145(1):59-68 (DOI:10.1080/00028487.2015.1094130) (2016). https://www.glerl.noaa.gov/pubs/fulltext/2016/20160019.pdf

Bioenergetics modeling was used to determine individual and population consumption by Bloater Coregonus hoyi in Lake Michigan during three time periods with variable Bloater density: 1993–1996 (high), 1998–2002 (intermediate), and 2009–2011 (low). Despite declines in Bloater abundance between 1993 and 2011, our results did not show any density-dependent compensatory response in annual individual consumption, specific consumption, or proportion of maximum consumption consumed. Diporeia spp. accounted for a steadily decreasing fraction of annual consumption, and Bloater were apparently unable to eat enough Mysis diluviana or other prey to account for the loss of Diporeia in the environment. The fraction of production of both Diporeia and Mysis that was consumed by the Bloater population decreased over time so that the consumption-to-production ratio for Diporeia C Mysis was 0.74, 0.26, and 0.14 in 1993–1996, 1998–2002, and 2009–2011, respectively. Although high Bloater numbers in the 1980s to 1990s may have had an influence on populations of Diporeia, Bloater were not the main factor driving Diporeia to a nearly complete disappearance because Diporeia continued to decline when Bloater predation demands were lessening. Thus, there appears to be a decoupling in the inverse relationship between predator and prey abundance in Lake Michigan. Compared with Alewife Alosa pseudoharengus, the other dominant planktivorein the lake, Bloater have a lower specific consumption and higher gross conversion efficiency (GCE), indicating that the lake can support a higher biomass of Bloater than Alewife. However, declines in Bloater GCE since the 1970s and the absence of positive responses in consumption variables following declines in abundance suggest that productivity in Lake Michigan might not be able to support the same biomass of Bloater as in the past.

Studies evaluating the impacts of dreissenid mussels in Lake Michigan have largely focused on changes in phytoplankton dynamics in the offshore region (i. e., > 100 m depth) even though mussel biomass is actually highest in mid-depth coastal regions of Lake Michigan (i. e., 30–50 m). Here we report on changes at the base of the food web during 1995–2014 at a mid-depth site located in southeastern Lake Michigan. Specifically, we evalu - ated trends in Secchi depth, surface mixed layer chlorophyll- a and total phosphorus (TP), sub-epilimnetic deep chlorophyll layer concentrations, and near bottom chlorophyll- a concentrations and whether there have been shifts in the seasonal patterns of these variables. Median chlorophyll- a concentrations declined over 63 % during the spring isothermal period following the sharp increase in mussel abundance between 1996–2002 and 2007–2014. Chlorophyll- a concentrations in the spring were generally between 2 and 3 mg m –3 in 1996–2002, but almost never exceeded 1 mg m –3 in 2007–2014. Secchi depths increased in all months between 1996–2002 and 2007–2014, with the greatest changes being observed in the spring. Total phosphorus in the surface mixed layer declined over the study period, but not at as fast a rate as chlorophyll- a, a change consistent with mussel invasions. There was a 90% decline in the median depth integrated deep chlorophyll- a concentration between 1995–2000 and 2007–2014 in June when this feature was at its peak. Chlorophyll- a concentrations in the near bottom zone also decreased over time, likely due to their constant contact with dreissenid mussels. The declines in chlorophyll- a and changes in nutrient dynamics at the mid-depth site are consistent with dreissenid induced impacts that have also been documented at deeper, offshore sites in Lake Michigan.

Recovering populations of piscivores can challenge understanding of ecosystem function due to impacts on prey and to potentially altered food webs supporting their production. Stocks of walleye (Percidae, Sander vitreus), an apex predator in the Laurentian Great Lakes, crashed in the mid-1900s. Management efforts led to recovery by 2009, but recovery coincided with environmental and fish community changes that also had implications for the feeding ecology of walleye. To evaluate potential changes in feeding ecology for this apex predator, we assessed diets in the main basin of Lake Huron and in Saginaw Bay, a large embayment of Lake Huron, during 2009–2011. Walleye switched their diets differently in the main basin and Saginaw Bay, with non-native round goby (Gobiidae, Neogobius melanostomus) and rainbow smelt (Osmeridae, Osmerus mordax) more prevalent in diets in the main basin, and invertebrates, yellow perch (Percidae, Perca flavescens) and gizzard shad (Clupeidae, Dorosoma cepedianum) more prevalent in diets in the bay. Feeding strategy plots indicated that there was a high degree of individual specialisation by walleye in the bay and the main basin. Bioenergetic simulations indicated that walleye in Saginaw Bay need to consume 10%–18% more food than a walleye that spends part or all of the year in the main basin, respectively, in order to achieve the same growth rate. The differences in diets between the bay and main basin highlight the flexibility of this apex predator in the face of environmental changes, but changes in diet can alter energy pathways supporting piscivore production.

Re-eutrophication and harmful algal blooms in Lake Erie have resulted in a renewed call for remedial measures such as reductions of phosphorus loads to the lake's western basin. The action of further nutrient reductions may also reduce the intensity of seasonal central basin hypolimnetic anoxia by reducing algal biomass. However, winter–spring blooms of diatoms have not been fully recognized as a source of algal biomass that might contribute significantly to summer hypoxia. We compared spring and summer phytoplankton abundance in central and western Lake Erie based on monitoring data to show that spring phytoplankton biovolume was 1.5- to 6-fold greater than summer biovolume and that most spring biovolume was composed of filamentous diatoms, primarily Aulacoseira islandica, that is likely supported by an increasing silica load from Lake Huron. The rise of silica export was attributed to the dreissenid mussel invasion and establishment that reduced diatom abundance in Lake Huron and thereby increased silica availability in the receiving water body of Lake Erie. The relationship between phosphorus and winter–spring diatom blooms was unclear, but diatoms probably contributed the majority of the algal biomass that accumulated annually in the hypolimnion of the central basin of Lake Erie. Remedial measures aimed at reducing hypoxia must consider the winter–spring phytoplankton bloom in Lake Erie as an important and reoccurring feature of the lake that delivers a considerable quantity of algal biomass to the profundal zone of the lake.

Cyanobacterial harmful algal blooms (CHABs) are a problem in western Lake Erie, and in eutrophic fresh waters worldwide. Western Lake Erie is a large (3000 km2), shallow (8 m mean depth), freshwater system. CHABs occur from July to October, when stratification is intermittent in response to wind and surface heating or cooling (polymictic). Existing forecast models give the present location and extent of CHABs from satellite imagery, then predict two-dimensional (surface) CHAB movement in response to meteorology. In this study, we simulated vertical distribution of buoyant Microcystis colonies, and 3-D advection, using a Lagrangian particle model forced by currents and turbulent diffusivity from the Finite Volume Community Ocean Model (FVCOM). We estimated the frequency distribution of Microcystis colony buoyant velocity from measured size distributions and buoyant velocities. We evaluated several random-walk numerical schemes to efficiently minimize particle accumulation artifacts. We selected the Milstein scheme, with linear interpolation of the diffusivity profile in place of cubic splines, and varied the time step at each particle and step based on the curvature of the local diffusivity profile to ensure that the Visser time step criterion was satisfied. Inclusion of vertical mixing with buoyancy significantly improved model skill statistics compared to an advection-only model, and showed greater skill than a persistence forecast through simulation day 6, in a series of 26 hindcast simulations from 2011. The simulations and in situ observations show the importance of subtle thermal structure, typical of a polymictic lake, along with buoyancy in determining vertical and horizontal distribution of Microcystis.

A 1-dimensional (vertical), linked hydrodynamic and eutrophication model that was previously calibrated and corroborated with 19 years (1987–2005) of observations in the central basin of Lake Erie, was applied as part of a group of models capable of forecasting ecosystem responses to altered phosphorus loads to Lake Erie. The results were part of the effort guiding the setting of new phosphorus loading targets in accordance with the Great Lakes Water Quality Agreement. Our analysis demonstrated that while reductions in total phosphorus loads can be expected to reduce hypoxia and chlorophyll-a impairments on average, climate and meteorological variability will result in significant year to year variability. We provide examples for achieving hypothetical water quality goals and relate the required reductions to recent nutrient sources.

The Walleye Sander vitreus is an important sport fish that has experienced low reproductive success in some Great Lakes tributaries since severe population declines began in the late 1940s. In the Muskegon River, a Lake Michigan tributary, natural reproduction of Walleyes remains low and is largely supplemented by stocking. We evaluated the influence of abiotic factors on Walleye reproductive success in the Muskegon River during April and May 2009 and 2010 by (1) estimating Walleye egg density and survival; (2) estimating the size, density, abundance, and survival of Walleye larvae; and (3) relating our estimates to physical habitat conditions. Egg densities were 70-fold higher in 2009 than in 2010, but eggs experienced colder water temperatures, higher river discharge rates, and lower survival in 2009 relative to 2010. Egg survival in incubators was positively related to temperature and negatively related to flow at most sites. In both years, Walleye larvae that hatched during periods of cooler temperature were smaller than larvae that hatched later during periods of warmer temperature. Walleye larval densities were highest near spawning grounds and decreased downstream. Bayesian estimates of variability in larval densities indicated that temporal variability was twice as high as spatial variability in the Muskegon River. Larval survival was much lower in 2009 than in 2010, resulting in an approximately sevenfold higher production of larvae in 2010 than in 2009. Survival was highest for smaller larvae that hatched early in April 2010, when temperatures were warm and discharges were low and stable; in contrast, survival was much lower for larger larvae hatching later in 2010 or for large and small larvae in 2009, when water temperatures were colder and discharges were higher and more variable. Our results suggest that abiotic factors, primarily temperature and river flow, likely control the early survival of Walleyes in the Muskegon River.

RUTHERFORD, E.S., and K.A. Rose. Individual-Based Model Analysis of Walleye and Yellow Perch Population Dynamics in Response to Changing Ecosystem Conditions. . In Oneida Lake: Long-term Dynamics of a Managed Ecosystem and Its Fishery. Edward L. Mills Lars G. Rudstam, James R. Jackson, and Donald J. Stewart. Published by the American Fisheries Society, Bethesda, MD, (2016).

Stocked and naturally reproducing salmonids in Lake Michigan support an economically important charter boat fishery which operates from multiple locations around the lake. Charter boat operators depend on the sustainability and spatial availability of salmonid species. We analyzed the spatial distributions of charter boat harvest of brown trout, Chinook salmon, coho salmon, lake trout, and rainbow trout from 1992 to 2012. We found that during this 21 year period fishing effort shifted closer to shore, to the west, and to the north. Harvest of some species, namely lake trout and rainbow trout, shifted towards shallower bottom depths and closer to shore. In contrast, harvests of Chinook and coho salmon have not shifted closer to shore in a consistent manner. We suggest that a variety of factors may have contributed to these trends in harvest patterns, including recent ecosystem shifts in Lake Michigan. While we acknowledge that spatial harvest patterns are unlikely to precisely mirror salmonid distribution patterns, we believe that reporting coarse shifts in harvest has implications for future management options including, but not limited to, stocking decisions and harvest regulations.

Growing demand from the general public for centralized points of data access and analytics tools coincides with similar, well-documented needs of regional and international hydrology research and resource management communities. To address this need within the Laurentian Great Lakes region, we introduce the Great Lakes Dashboard (GLD), a dynamic web data visualization platform that brings multiple time series data sets together for visual analysis and download. The platform's adaptable, robust, and expandable Time Series Core Object Model (GLD-TSCOM) separates the growing complexity and size of Great Lakes data sets from the web application interface. Although the GLD-TSCOM is currently applied exclusively to Great Lakes data sets, the concepts and methods discussed here can be applied in other geographical and topical areas of interest.

Communities of organisms, from mammals to microorganisms, have discontinuous distributions of body size. This pattern of size structuring is a conservative trait of community organization and is a product of processes that occur at multiple spatial and temporal scales. In this study, we assessed whether body size patterns serve as an indicator of a threshold between alternative regimes. Over the past 7000 years, the biological communities of Foy Lake (Montana, USA) have undergone a major regime shift owing to climate change. We used a palaeoecological record of diatom communities to estimate diatom sizes, and then analysed the discontinuous distribution of organism sizes over time. We used Bayesian classification and regression tree models to determine that all time intervals exhibited aggregations of sizes separated by gaps in the distribution and found a significant change in diatom body size distributions approximately 150 years before the identified ecosystem regime shift. We suggest that discontinuity analysis is a useful addition to the suite of tools for the detection of early warning signals of regime shifts.

Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments – since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins – especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll-a (Chl-a) or phycocyanin (PC) collected in situ as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl-a. Where cyanobacteria dominate, Chl-a is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MCpigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl-a concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameteriza- tions between lakes. A strategy for producing useful estimates of microcystins from cyanobacterial biomass is described, provided cyanotoxin variability is addressed.

The Great Lakes are host to thousands of native fishes, invertebrates, plants, and other species that not only provide recreational and economic value to the region, but also hold important ecological value. However, with over 180 documented aquatic nonindigenous species1 (ANS) and an apparent introduction rate estimated at 1.3-1.8 species·year-1 through 2006, the Great Lakes basin is considered one of the most heavily invaded aquatic systems in the world (Mills et al. 1993, Ricciardi 2006, GLRI Task Force 2010). Some of these nonindigenous species may become invasive (i.e. “species whose introduction does or is likely to cause economic or environmental harm or harm to human health” (Executive Order 13112, 1999)) and threaten the ecological and/or socio-economic value of the Great Lakes. In contrast, other nonindigenous species are capable of contributing value to the Great Lakes. Pacific salmonids, for instance, are stocked annually by the millions to help support the Great Lakes’ multi-billion dollar fishery (Kocik and Jones 1999, USFWS/GLFC 2010, USACE 2012a).

This study provides a snapshot of management of established nonindigenous species in the Great Lakes region as a benchmark for improving management practices. We review the relevant state and federal regulations that impact AIS management as well as management alternatives in a format that allows cross-jurisdictional and cross-taxa analysis. This effort is part of a larger project funded by the Great Lakes Restoration Initiative to enhance the Great Lakes Aquatic Nonindigenous Species Information System (GLANSIS1), an online database containing information on the identification, distribution, ecology, impact, and management of all established ANS in the Great Lakes. Previously, we assessed the relative ecological and socioeconomic impacts of nonindigenous species (NOAA Technical Memorandum 161 – An Impact Assessment of Great Lakes Aquatic Nonindigenous Species; Sturtevant et al. 2014).

Detection of invasive species before or soon after they establish in novel environments is critical to prevent widespread ecological and economic impacts. Environmental DNA (eDNA) surveillance and monitoring is an approach to improve early detection efforts. Here we describe a large-scale conservation application of a quantitative polymerase chain reaction assay with a case study for surveillance of a federally listed nuisance species (Ruffe, Gymnocephalus cernua) in the Laurentian Great Lakes. Using current Ruffe distribution data and predictions of future Ruffe spread derived from a recently developed model of ballast-mediated dispersal in US waters of the Great Lakes, we designed an eDNA surveillance study to target Ruffe at the putative leading edge of the invasion. We report a much more advanced invasion front for Ruffe than has been indicated by conventional surveillance methods and we quantify rates of false negative detections (i.e. failure to detect DNA when it is present in a sample). Our results highlight the important role of eDNA surveillance as a sensitive tool to improve early detection efforts for aquatic invasive species and draw attention to the need for an improved understanding of detection errors. Based on axes that reflect the weight of eDNA evidence of species presence and the likelihood of secondary spread, we suggest a two-dimensional conceptual model that management agencies might find useful in considering responses to eDNA detections.

Climate change is likely to stimulate the development of harmful cyanobacterial blooms in eutrophic waters, with negative consequences for water quality of many lakes, reservoirs and brackish ecosystems across the globe. In addition to effects of temperature and eutrophication, recent research has shed new light on the possible implications of rising atmospheric CO2 concentrations. Depletion of dissolved CO2 by dense cyanobacterial blooms creates a concentration gradient across the air–water interface. A steeper gradient at elevated atmospheric CO2 concentrations will lead to a greater influx of CO2, which can be intercepted by surface-dwelling blooms, thus intensifying cyanobacterial blooms in eutrophic waters. Bloom-forming cyanobacteria display an unexpected diversity in CO2 responses, because different strains combine their uptake systems for CO2 and bicarbonate in different ways. The genetic composition of cyanobacterial blooms may therefore shift. In particular, strains with high-flux carbon uptake systems may benefit from the anticipated rise in inorganic carbon availability. Increasing temperatures also stimulate cyanobacterial growth. Many bloom-forming cyanobacteria and also green algae have temperature optima above 25 8C, often exceeding the temperature optima of diatoms and dinoflagellates. Analysis of published data suggests that the temperature dependence of the growth rate of cyanobacteria exceeds that of green algae. Indirect effects of elevated temperature, like an earlier onset and longer duration of thermal stratification, may also shift the competitive balance in favor of buoyant cyanobacteria while eukaryotic algae are impaired by higher sedimentation losses. Furthermore, cyanobacteria differ from eukaryotic algae in that they can fix dinitrogen, and new insights show that the nitrogen-fixation activity of heterocystous cyanobacteria can be strongly stimulated at elevated temperatures. Models and lake studies indicate that the response of cyanobacterial growth to rising CO2 concentrations and elevated temperatures can be suppressed by nutrient limitation. The greatest response of cyanobacterial blooms to climate change is therefore expected to occur in eutrophic and hypertrophic lakes.

Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

In this study, temporal variability of ice cover in the Great Lakes is investigated using historical satellite measurements undated from 1973 to 2015. With high ice cover in the last two winters (2013/14 and 2014/15), the trend was significantly reduced, compared to the period 1973-2013. The decadal variability in lake ice attributed to the decreased trend. It was found that 1) Great Lakes ice cover has a linear relationship with Atlantic Multidecadal Oscillation (AMO), similar to the relationship of lake ice cover with the North Atlantic Oscillation (NAO), and 2) a weak quadratic relation with the Pacific Decadal Oscillation (PDO), similar to the relationship of lake ice cover with the Niño3.4. Based on these dynamic relationships, the original multiple variable regression models established using the indices of NAO and Niño3.4 is updated by adding both AMO and PDO, as well their competing mechanism. With the AMO and PDO added, the correlation between the model and observation increases to 0.68, compared to 0.44 using NAO and Niño3.4 only. The new model was used to project the annual maximum ice coverage using projected indices of Niño3.4, NAO, PDO, and AMO. On November 30, 2015, the AMIC of 2015/16 winter was projected to be 31%.

This article presents a comprehensive analysis of interannual and interdecadal variations of summer precipitation and precipitation-related extreme events in East China associated with variations of the East Asian summer monsoon (EASM) from 1979 to 2012. A high-quality daily precipitation data set covering 2076 observational stations in China is analysed. Based on the precipitation pattern analysis using empirical orthogonal functions and the regime shift detection method, three sub-periods of 1979–1992 (period I), 1993–1999 (period II) and 2000–2012 (period III) are identified to be representative of the precipitation variability. Similar significant variability of the extreme precipitation indices is found across four sub-regions in eastern China. The spatial patterns of summer mean precipitation, the number of days with daily rainfall exceeding 95th percentile precipitation (R95p) and the maximum number of consecutive wet days (CWD) anomalies are consistent, but opposite to that of maximum consecutive dry days (CDD) anomalies to some extent during the three sub-periods. However, the spatial patterns of hydroclimatic intensity (HY-INT) are notably different from that of the other three extreme indices, but highly correlated to the dry events. The changes of precipitation anomaly patterns are accompanied by the change of the EASM regime and the abrupt shift of the position of the west Pacific subtropical high around 1992/1993 and 1999/2000, respectively, which influence the moisture transport and contributes to the precipitation anomalies. In addition, the EASM intensity is linked to sea surface temperature anomaly over the tropical Indian and Pacific Ocean through its effects on convective activity over the west Pacific that induces the cyclonic or anticyclonic anomaly over the South China and northwest Pacific.

In this study, a one-dimensional (1-D) thermal diffusion lake model within the Weather Research and Forecasting (WRF) model was investigated for the Laurentian Great Lakes. In the default 10-layer lake model, the albedos of water and ice are specified with constant values, 0.08 and 0.6, respectively, ignoring shortwave partitioning and zenith angle, ice melting, and snow effect. Some modifications, including a dynamic lake surface albedo, tuned vertical diffusivities, and a sophisticated treatment of snow cover over lake ice, have been added to the lake model. A set of comparison experiments have been carried out to evaluate the performances of different lake schemes in the coupled WRF-lake modeling system. Results show that the 1-D lake model is able to capture the seasonal variability of lake surface temperature (LST) and lake ice coverage (LIC). However, it produces an early warming and quick cooling of LST in deep lakes, and excessive and early persistent LIC in all lakes. Increasing vertical diffusivity can reduce the bias in the 1-D lake but only in a limited way. After incorporating a sophisticated treatment of lake surface albedo, the new lake model produces a more reasonable LST and LIC than the default lake model, indicating that the processes of ice melting and snow accumulation are important to simulate lake ice in the Great Lakes. Even though substantial efforts have been devoted to improving the 1-D lake model, it still remains considerably challenging to adequately capture the full dynamics and thermodynamics in deep lakes.

The variability of East Asian upper level westerly jets in winter is studied with regard to the concurrent existence of subtropical jet (East Asian subtropical jet (EASJ)) and polar-front jet (East Asian polar-front jet (EAPJ)) using the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis. In the distribution of jet occurrence revealed in 6-hourly data, two jet branches along 30°N and 55°N, corresponding to locations of EASJ and EAPJ, respectively, are separated over the Tibetan Plateau. The leading two modes of zonal-mean zonal wind in East Asia extracted from a mass-weighted empirical orthogonal function analysis are characterized by the intensity changes and location displacements of two jets. The key regions for EASJ and EAPJ are then defined to represent variabilities of these two jets. Correlation analysis indicates that the subseasonal variation of EAPJ precedes EASJ by around 5 days, which can be interpreted as wave-mean flow interactions via synoptic-scale transient eddy activities. Based on the pentad intensity indices of two jets, the concurrent variabilities of EASJ and EAPJ are investigated with typical temperature and precipitation anomalies in China. The results suggest that by taking account of the two jets, we are able to get a more comprehensive understanding of the winter climate.

Accurate representations of lake-ice-atmosphere interactions in regional climate modeling remain one of the most critical and unresolved issues for understanding large-lake ecosystems and their watersheds. To date, the representation of the Great Lakes two-way interactions in regional climate models is achieved with 1-D lake models applied at the atmospheric model lake grid points distributed spatially across a 2-D domain. While some progress has been made in refining 1-D lake model processes, such models are fundamentally incapable of realistically resolving a number of physical processes in the Great Lakes. In this study we develop a two-way coupled 3-D climate-lake-ice modeling system (named TC-3D-GLARM) aimed at improving the simulation of large lakes in regional climate models and accurately resolving the hydroclimatic interactions. Model results are compared to a wide variety of observational data and demonstrate the unique skill of the coupled 3-D modeling system in reproducing trends and variability in the Great Lakes regional climate, as well as in capturing the physical characteristics of the Great Lakes by fully resolving the lake hydrodynamics. Simulations of the climatology and spatiotemporal variability of lake thermal structure and ice are significantly improved over previous coupled, 1-D simulations. At seasonal and annual time scales, differences in model results are primarily observed for variables that are directly affected by lake surface temperature (e.g., evaporation, precipitation, and sensible heat flux) while no significant differences are found in other atmospheric variables (e.g., solar radiation, cloud cover). Underlying physical mechanisms for the simulation improvements using TC-3D-GLARM are also discussed.

Nonindigenous bigheaded carps (Bighead Carp Hypophthalmichthys nobilis and Silver Carp H. molitrix; hereafter, “Asian carps” [AC]) threaten to invade and disrupt food webs and fisheries in the Laurentian Great Lakes through their high consumption of plankton. To quantify the potential effects of AC on the food web in LakeErie, we developed an Ecopath with Ecosim (EwE) food web model and simulated four AC diet composition scenarios (high, low, and no detritus and low detritus with Walleye Sander vitreus and Yellow Perch Perca flavescens larvae) and two nutrient load scenarios (the 1999 baseline load and 2£ the baseline [HP]). We quantified the uncertainty of the potential AC effects by coupling the EwE model with estimates of parameter uncertainty in AC production, consumption, and predator diets obtained using structured expert judgment. Our model projected

mean § SD AC equilibrium biomass ranging from 52 § 34 to 104 § 75 kg/ha under the different scenarios. Relative to baseline simulations without AC, AC invasion under all detrital diet scenarios decreased the biomass of most fish and zooplankton groups. The effects of AC in the HP scenario were similar to those in the detrital diet scenarios except that the biomasses of most Walleye and Yellow Perch groups were greater under HP because these fishes were buffered from competition with AC by increased productivity at lower trophic levels. Asian carp predation on Walleye and Yellow Perch larvae caused biomass declines among all Walleye and Yellow Perch groups. Large food web impacts of AC occurred in only 2% of the simulations, where AC biomass exceeded 200 kg/ha, resulting in biomass declines of zooplankton and planktivorous fish near the levels observed in the Illinois River. Our findings suggest that AC would affect Lake Erie’s food web by competing with other planktivorous fishes and by providing additional prey for piscivores. Our methods provide a novel approach for including uncertainty into forecasts of invasive species’ impacts on aquatic food webs.

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